Digital Commons Network^™

Examining Ai Use Strategies Among Engineering Students: An Exploratory Quantitative Study, Jenny Lee Blonquist

All Graduate Theses and Dissertations, Fall 2023 to Present

Artificial intelligence tools like ChatGPT have quickly become part of everyday life for many people, including engineering students. This has raised concerns about the effects of students relying or over-relying on AI to help with their coursework. Are they still building the problem-solving and reasoning skills they will need as engineers? The purpose of this study is to understand not just whether engineering students use AI, but how they use it.

This research focused on two different ways students can use AI tools. 'Understanding-seeking' is when a student uses AI as a learning support such as asking thoughtful questions to …

Global, Regional, And National Burden Of Hiv/Aids, 1990–2023, With The Estimated Burden Attributable To Intimate Partner Violence And Forecasted Impacts Of Funding Cuts Through 2030: Results From The Global Burden Of Disease Study 2023, Austin Carter, Meixin Zhang, Bricia G. Trejo, Megan Verma, Edmond D. Brewer, Dylan Lasher, Jiawei He, Regina Mae Villanueva Dominguez, Amanda Movo, Jianing Ma, Olivia Angelino, Hans J. Elliott, Carolyn M. Shyong, Ian E. Cogswell, Abdullah, Hasan Aalruz, Mulatu Abageda, Ukachukwu O. Abaraogu, Qamar Abbas, Samar Abd Elhafeez, Ashraf Nabiel Abdalla, Emad M. Abdallah, Reda Abdel-Hameed, Siddig Ibrahim Abdelwahab, Wakgari Mosisa Abdisa, Meriem Abdoun, Arman Abdous, Zahir Vally

All Works

Background Despite a general improvement in the HIV burden over the past two decades, gendered social determinants including intimate partner violence (IPV) continue to affect women's vulnerability to HIV, which could be further exacerbated as resources dwindle over the coming years. Our study aimed to quantify recent trends in the HIV burden, the magnitude of the HIV burden associated with IPV, and the potential impact of declining financial support globally. Methods Using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework, we estimated annual HIV incidence, prevalence, and mortality for 204 countries and territories from 1990 …

Improving Tensorsketch Using Complex Random Variables, Amit Sharma, Mohammad Azhar Khan, Rameshwar Pratap, Keegan Kang

Faculty Conference Papers and Presentations

TensorSketch by Pham and Pagh [2013], Kar and Karnick [2012] provides efficient sketching algorithms for highdimensional polynomial kernels $\vec{x}^{\otimes p} \in \R^{d^p}$. Kar and Karnick [2012] uses dense Johnson-Lindenstrauss (JL)-type projections with computational cost $O(pDd)$, whereas Pham and Pagh [2013] extends the sparse CountSketch [Charikar et al., 2024] algorithm, yielding a faster algorithm for high-dimensional sparse inputs with running time $O\left(p(\nnz{\vec{x}} + D \log D)\right)$. However, the variance of both estimators grows exponentially with the polynomial degree $p$, scaling as $3^{p}/D$, where $D$ denotes the sketch dimension. Recent work by Wacker et al. [2023] showed that using complex-valued distribution reduces …

A Blockchain-Enabled Framework For Transparent Carbon Accounting In Global Supply Chains Using Multi-Regional Input–Output (Mrio) Analysis, Pratyush Kumar Patro, Adolf Acquaye, Khaled Salah, Raja Jayaraman

Industrial Engineering: Faculty & Staff Publications

No abstract provided.

Dbssnet: Dual-Branch Spectral-Spatial Network With Data-Driven And Knowledge-Guided Band Selection For Uav Hyperspectral Wheat Rust Detection, Subin Kim

All Graduate Theses and Dissertations, Fall 2023 to Present

Wheat rust is a serious plant disease that can reduce crop yield and quality. In practice, the disease is often noticed only after visible symptoms appear, when some damage may already be difficult to reverse. This thesis studies whether drone-based imaging can help detect wheat rust earlier and more reliably in field environments. 

Unlike an ordinary color photograph, a hyperspectral image records reflected light at many narrow wavelengths. These measurements can reveal useful information about plant condition, but they are also high dimensional, noisy, and difficult to analyze when only a limited number of labeled field samples are available. To …

Viability Assessment Of Bovine Embryos: A Public Dataset And Deep Learning Baselines, Erfan Khayyati

All Graduate Theses and Dissertations, Fall 2023 to Present

Improving the success rates of cattle breeding is essential for sustainable agriculture, global food security, and high-quality livestock production. Currently, determining whether a lab-grown bovine embryo is healthy enough for a successful pregnancy requires highly trained experts to manually evaluate days of continuous time-lapse video footage. This process is not only incredibly time-consuming but also highly subjective; human reviewers often suffer from visual fatigue when tracking subtle, microscopic cellular changes over a seven-day period, leading to significant disagreement among even top experts on an embryo’s true potential. Furthermore, assessing bovine embryos is notoriously difficult due to their dark, lipid-dense cellular …

Secure Agricultural Futures: Re-Defining And -Imagining Agricultural Water Landscapes In The Us West, Britta L. Schumacher

All Graduate Theses and Dissertations, Fall 2023 to Present

Aridity is swiftly becoming the US West’s new normal. As agricultural communities adjust to persistent growing-season scarcity, they find their livelihoods under increasing threat. This points to the urgency of finding paths toward more secure water futures. A piece of this future puzzle includes water (re-)distribution – taking excess from one place and delivering it to another in need. To begin thinking about (re-)distribution, this dissertation engages with three mixed-methods and multiscale studies. The first study pairs county-level data across the 11 westernmost US states with survey data collected from individual producers in Utah to assess past and current trends …

A Multi-Label Computer Vision-Based Approach For Condition Assessment Of Traffic Signs: Database Compilation, Model Training, And Evaluation, Shailaja Ratna Pandey

All Graduate Theses and Dissertations, Fall 2023 to Present

Traffic signs help drivers and pedestrians to understand roadway rules, warnings, and directions, which determine how road users should behave. When signs fade or delaminate, they become harder to read and interpret, which creates increased safety hazards. Transportation agencies usually deploy engineers to the field to inspect signs because they need to evaluate and document the sign’s condition based on established standards and engineering judgment. This process requires substantial time and cost and becomes challenging to apply across large highway networks.

This study evaluated two computer vision (CV) models for automated traffic sign condition assessment using highway images collected across …

From Evidence To Impact: Supporting Sensemaking And Instructional Revision In Stem Classrooms, Bonni Jones

All Graduate Theses and Dissertations, Fall 2023 to Present

Science and math literacy is crucial for informed citizenship and economic competitiveness, yet many students leave school without developing the critical thinking skills needed to understand and solve complex issues or pursue STEM careers. This disconnect often stems from traditional teaching methods that emphasize memorization and following steps over authentic reasoning and problem solving. This dissertation addresses this challenge by identifying how teachers in research studies have taught STEM in ways that develop students' ability to think, reason, and problem-solve like real scientists.

By analyzing research on instruction that incorporates modeling, inquiry, and sensemaking, and working directly with teachers, this …

Causal Discovery In Photospheric Magnetic Field Time Series For Interpretable Solar Flare Prediction, Nathan W. Nelson

All Graduate Theses and Dissertations, Fall 2023 to Present

Solar flares are capable of damaging many valuable resources, including satellites, power grids, and even human lives. Being able to predict solar flares can allow for proactive measures to be taken that can prevent that damage. Many new deep learning methods for predicting solar flares have shown promise in this task, but the decisions they make are harder to explain to humans. This makes understanding why these models make mistakes difficult, which in turn makes fixing and maintaining them more challenging. We test a recent deep learning method that helps discover relationships between different measurements of the Sun as they …

Affective And Cognitive Factors Contributing To Male-Female Differences In Mathematics, Sarah N. Herod

All Graduate Theses and Dissertations, Fall 2023 to Present

Math differences between men and women have been studied for several decades, with original theories suggesting a biological reason for the differences and more new ones suggesting multiple factors, such as self-efficacy, anxiety, and spatial ability, may be responsible for these apparent differences. Additionally, most research into math differences between the sexes involves the use of a composite score, rather than examining the different sub-domains of math separately. The purpose of the current study was to examine the relationship between sex and math performance within the context of an individual's belief and attitudes towards math and spatial information. Seventy-one participants …

Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy, Kinspride K. Duah

All Graduate Theses and Dissertations, Fall 2023 to Present

Environmental decisions such as infrastructure design, water management, and snow load estimation depend on spatial data that are often incomplete or uncertain. In many cases, measurements are not exact values but ranges, reflecting limitations in data collection methods. Traditional mapping techniques typically simplify these uncertain measurements, which can lead to less accurate predictions. This dissertation introduces improved statistical tools for making spatial predictions when data are uncertain or partially known. By utilizing a framework called Bayesian Maximum Entropy (BME), this research demonstrates how exact measurements and range-based data can be combined in a mathematically consistent way. The work demonstrates that …

High-Throughput Characterization Of Creep In Additively Manufactured 316l Stainless Steel, Raushan Kumar Singh

All Graduate Theses and Dissertations, Fall 2023 to Present

Advanced materials are widely used in industries such as nuclear energy, aerospace, and automotive engineering, where components are exposed to extreme temperatures and stresses over long periods of time. As new materials continue to emerge, researchers need efficient ways to evaluate their mechanical performance so they can be used safely and effectively. Among several mechanical challenges, creep is a major concern in these conditions. Creep is a type of mechanical failure in which materials gradually deform when exposed to high temperatures and constant load. Conventional methods for evaluating creep typically involve testing a single specimen at a time, which can …

Faculty Perspectives On Career And Technical Education Programming For Prison And Other At-Risk Populations: Implications Of A Human Centered Design Focus, Taija R. Jackson

All Graduate Theses and Dissertations, Fall 2023 to Present

The purpose of this quantitative, cross-sectional, quasi-experimental study was to examine the perceptions of career and technical education (CTE) faculty regarding their familiarity with human-centered design (HCD), perceptions of the value and worth as a framework for program and curriculum design and willingness to teach in correctional education settings. The survey was administered to postsecondary CTE employed at public community and technical colleges in Utah and Colorado (N = 37). Participants were randomly assigned to either a treatment condition, in which they viewed a six-minute-long video vignette illustrating HCD in practice, or a control condition without exposure to the …

Thermal Rating And Prediction Of Roadway-Embedded Power Electronics For Dynamic Wireless Power Transfer, Forrest D. Nichols

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles can be charged while driving through wireless charging coils buried in the road surface. To avoid running expensive cables from roadside equipment to each charging pad, the electronics that control the power transfer can also be buried in the road. However, burying these circuit boards removes the ability to cool them with fans or flowing air, so the heat generated during operation must escape naturally into the surrounding road material. If the boards get too hot, components fail—a problem that has already been observed in prototype systems.

Predicting how hot each component on a circuit board will get …

Cadmium Biosorption By Fusarium Venenatum And Its Application In Functional Permeable Materials For Metal Removal, Bradley Lawson

All Graduate Theses and Dissertations, Fall 2023 to Present

Heavy metals are pollutants of increasing concern as continued industrialization and urbanization have escalated the discharge of these toxins into aquatic environments. Cadmium (Cd) is a metal of particular concern due to its acute toxicity and high mobility in aquatic ecosystems. Given these characteristics Cd poses significant health risks to both humans and aquatic ecosystems. The continued development of sustainable, low-cost remediation technology is imperative to manage metal pollution.

This research explores the use of fungal-based remediation systems to remove Cd from contaminated water. Living biomass of the filamentous fungus Fusarium venenatum was evaluated as a biosorbent material for Cd …

Diabetter Together: Outcomes Of A Randomized Controlled Trial Evaluating A Peer Mentor Behavioral Intervention For Young Adults With Type 1 Diabetes During The Transfer From Pediatric To Adult Care, Marisa E Hilliard, Charles G Minard, Samantha A Carreon, Wendy L Levy, Sarah K Lyons, Randi Streisand, Tricia S Tang, Siripoom V Mckay, Sridevi Devaraj, Barbara J Anderson

Faculty, Staff and Students Publications

Objective: Transition between pediatric and adult health care is complex, with high risk for loss to follow-up and suboptimal health outcomes for young adults with type 1 diabetes. This trial evaluated the efficacy of DiaBetter Together, a 12-month strengths-based behavioral intervention delivered by trained peer mentors. The intervention aimed to help young adults navigate the transfer process to promote optimal glycemic outcomes, shorten time to adult care follow-up, and improve psychosocial outcomes.

Research design and methods: Using a single-site randomized clinical trial design, we compared the 12-month intervention to usual care among n = 100 young adults aged 17-25 years …

Quantitative Imaging Of Pyruvate Metabolism In A Patient With Anaplastic Thyroid Cancer, James A Bankson, Joshua S Niedzielski, Collin J Harlan, Yunyun Chen, Christopher M Walker, Philip L Lorenzi, Lin Tan, Vikas Kundra, Matthew E Merritt, Mukundan Ragavan, Dawid Schellingerhout, Renjie He, Yao Ding, Sahana Datar, Qing Wang, Christine B Peterson, Clifton D Fuller, Vlad C Sandulache, Stephen Y Lai

Faculty, Staff and Students Publications

Purpose: Magnetic resonance imaging using hyperpolarized (HP) [1-13C]-pyruvate enables assessment of pyruvate metabolism in vivo and offers new insight into metabolic changes in response to cancer therapy. Widely used semi-quantitative metrics of pyruvate metabolism can be affected by physiological factors that are extrinsic to intracellular metabolism. A validated pharmacokinetic (PK) model for analysis of intracellular pyruvate metabolism is needed to enhance the accuracy of quantitative metrics and clinical translation of metabolic MRI using HP pyruvate.

Methods: A PK model with two physical compartments and two chemical pools was developed to analyze the conversion of labeled pyruvate into lactate in vitro. …

Agronomic And Economic Evaluation Of Alternative Forage Crops Under Irrigation Technologies And Deficit Irrigation, Shikha Sharma

All Graduate Theses and Dissertations, Fall 2023 to Present

Water is becoming more limited in the western United States, including Utah, so farmers need forage crops that can produce well while using less irrigation water. This study examined how different forage crops respond to reduced irrigation and different irrigation application methods, and whether some crops can provide better economic returns under limited water conditions.

Field studies were conducted at three Utah locations, Cedar City, Logan, and Vernal, from 2020 to 2024. The alternative forage crops included teff, sorghum-sudangrass (sudex), and forage rye. For economic comparison, conventional forage crops included alfalfa, corn, and three-way small grains. Four to five irrigation …

2026 Summer Commencement Program, The University Of West Alabama

Commencement Programs

No abstract provided.

Our Honors Impact: Evidence Of Honors Student Experience And Outcomes, 01 - The Initial Evidence Review, Brian Hoey, Honors College

Publications of the Honors College at Marshall University

Our Honors Impact, 01: Evidence of Honors Student Experience and Outcomes presents an initial review of student-centered evidence collected by the Honors College at Marshall University through its developing Honors Impact Evidence Bank. Drawing on student reflections, supported-project deliverables, program assessments, profiles, and other documented experiences, the report examines how honors education is experienced in practice and what becomes possible through integrative and experiential learning, mentorship, peer connection, financial support, global engagement, and opportunities for independent inquiry. Student narratives illustrate recurring patterns of intellectual growth, confidence, belonging, professional development, and connection to Appalachia and West Virginia. As the first edition …

The Effects Of Education And Training On Clinical Staff’S Knowledge, Perception, And Clinical Practice Of The Medication Reconciliation Process, Stephanie A. Williams

Doctor of Nursing Practice Projects

Medication-related harm affects approximately one in 30 patients in healthcare settings. Accurate medication reconciliation (MedRec) is essential for identifying medication discrepancies, preventing medication errors, and reducing adverse drug events. Clinical staff play a critical role in ensuring the accuracy of medication lists in primary care settings.

This evidence-based quality improvement project evaluated the effect of a structured MedRec training intervention on MedRec knowledge, perceptions, and practices among clinical staff in a primary care clinic in Southeast Texas. The project used a single-group, quantitative, quasi-experimental design. A convenience sample of 32 clinical staff members completed knowledge and perception assessments before and …

Llm-Assisted Task-Adaptive Semantic Communication Over Non-Ideal Channels For Vision–Language Systems, Oluwagbenga Oluwapelumi Orimoogunje

All Theses

The growth of intelligent wireless systems and bandwidth-limited edge devices has created a need for communication methods that move beyond bit-level data transmission. Semantic communication addresses this by transmitting task-relevant meaning, which reduces bandwidth usage while preserving task performance. However, existing approaches often rely on frozen encoders without task feedback and are trained under fixed or ideal signal-to-noise ratio (SNR) conditions. These limitations lead to poor generalization in realistic noisy channels.

This thesis proposed a task-adaptive semantic communication framework for Visual Question Answering (VQA) over bandwidth-constrained Additive White Gaussian Noise (AWGN) channels. The system transmits a compact 16,384-dimensional semantic feature …

Effective Data Augmentation Strategies For Small Object Detection, Tarek Aziz

All Theses

Data augmentation remains the most effective method of improving object detection, particularly in scenes where small objects dominate, and the annotated datasets are small. While geometric augmentation techniques such as flipping, cropping, and photometric augmentations such as brightness, color jittering adjustments, and content-level augmentations such as mix-up and copy-paste augmentation have proved useful, current research suggests the viability of learned augmentation policies, instance-level generative augmentations, and diffusion-based augmentations. Here, we present a structured comparison of the augmentation methods on the YOLO11m detector, focusing particularly on the detection of small objects on the SODA-D dataset. We benchmarked the standard YOLO11m model …

A Comparison Of Survival, Growth, And Stress Resilience In Three Different Lineages Of The Pacific Oyster (Crassostrea Gigas) Farmed On The California Central Coast, Victoria F. Hanshaw

Master's Theses

Aquaculture of Pacific oysters on the US West Coast is routinely impacted by seasonal unexplained mortality events. To better understand these large-scale mortality events in oyster aquaculture, shellfish growers and scientists in California have partnered together to conduct comparative, multi-estuary farm trials of discrete Pacific oyster (Crassostrea gigas) lineages. In this thesis we investigate how the more recently imported Midori lineage performs compared to the historically used Miyagi lineage, as well as a Hybrid (Midori x Miyagi) lineage. As part of a 7-month long field study from April-November of 2024 in Morro Bay and Tomales Bay, California, we evaluated …

Electromagnetic Enhancement Of A Potassium-Seeded Rotating Detonation Engine, Anthony Joseph Presto Jr.

Master's Theses

Rotating detonation engines offer a route to pressure-gain combustion by sustaining one or more detonation waves in an annular chamber supplied by continuous propellant injection. This thesis evaluates whether potassium seeding can make the high-temperature product flow of a hydrogen–air rotating detonation engine conductive enough to serve as the working fluid for magnetohydrodynamic acceleration. To the author’s best knowledge, the complete configuration modeled here has not been reported previously in open literature. This configuration consists of a hydrogen–air RDE with KOH-based potassium seeding, local conductivity estimates, and imposed Lorentz-force acceleration. The thesis therefore develops an initial computational model for this …

Prompt-Driven Tabletop Robotic Manipulation With A Structured Llm Interface And Visual Verification, Tomas Franco

Master's Theses

Creating a tabletop robotic manipulation system that connects language goals to robot actions is a challenging problem. Large language models can interpret mission objectives and reason through actions, but when placed directly in control of hardware they can produce hallucinated commands that result in unsafe behavior without the proper safeguards.

This thesis presents a constrained LLM-guided manipulation system built around the Quanser Qarm, a four degree of freedom manipulator with a mounted Realsense RGB-D camera and a gripper with readable current. Every decision made by the LLM planner is routed through a gated command interface that restricts the model to …

Sentinel: Evaluating Occlusion-Centered Next-Best-View Selection Using Rgb-Derived Pseudo-Geometry, Paul Nassar

Master's Theses

Three-dimensional cameras provide direct geometric measurements, but their cost, weight, power requirements, and calibration constraints can limit their use in various lightweight or large-scale sensing systems. A potential alternative is to use conventional two-dimensional RGB cameras together with geometric reconstruction models that infer a partial three-dimensional representation from images. This thesis evaluates that possibility for next-best-view (NBV) selection through Sentinel, an occlusion-centered system for static, object-centric scenes with known camera poses and intrinsics. Sentinel converts source RGB observations into pseudo-geometry using monocular depth or point-map predictions, combines those predictions with camera-ray evidence, identifies occluded unknown regions, and selects a candidate …

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …